1. Field of the Invention
The present disclosure relates to a recommender system. More specifically, the present disclosure relates to a technique that improves recommendations for a user by learning the user's activity preferences from unlabeled location traces (such as GPS readings) associated with the user's past activities and a set of records containing information about venues (such as restaurants, offices, etc) in the area where the GPS traces are recorded.
2. Related Art
In today's technologically-oriented society, a primary source of information is recommender systems. The purpose of most recommendation systems is to help individuals discover items they might not necessarily be able to find on their own. Such a recommender system can generate personalized recommendations in response to a query from a user. Effective recommendations often depend on how accurately the system can estimate a user's needs and preferences. Some systems, such as online shopping sites, use user surveys or a user's past selections to derive such information. However, it would be difficult to gather this information in a system with limited access to a user's selection history, or where user surveys are difficult to obtain.